Reception of co-channel signals

ABSTRACT

System ( 100 ) and methods ( 3500 ) for receive processing of a burst communication system where co-channel signals ( 318 ) collide in a receiver ( 150 ). The methods comprise: simultaneously receiving co-channel signals ( 2002, 2004, 2006 ) transmitted from remote transmitters ( 104 - 112 ) at a first frequency; and independently performing a first iteration of a Turbo MUD process for a first co-channel signal and a second co-channel signal. The Turbo MUD process comprises: segmenting each of the first and second co-channel signals into a plurality of segments ( 2102, 2104, 2106 ) each having a unique SINR; computing a noise plus interference variance estimate for each segment; computing first bit likelihood values for each segment based on the noise variance estimate; computing second bit likelihood values for each segment based on the first bit likelihood values; and using the second bit likelihood values (i.e., soft in soft-out) to generate a first estimate of the first and second co-channel signals.

STATEMENT OF THE TECHNICAL FIELD

The inventive arrangements relate to systems and methods for Multi-UserDetection (“MUD”). More particularly, the inventive arrangements concernTurbo Single-Input, Single-Output (“SISO”) MUD methods for burstcommunication systems where multiple signals collide in a receiver. Inthe following, these methods are referred to as Turbo MUD processing, ora Turbo MUD process. The algorithm or device that performs these methodsis referred to as a Turbo MUD processor.

DESCRIPTION OF THE RELATED ART

A Single-Input, Single-Output (“SISO”) communication system employs asingle transmit antenna per user and a single receive antenna for datatransmission. A Single-Input, Multiple-Output (“SIMO”) communicationsystem employs a single transmit antenna per user and multiple receiveantennas for data transmission. A Multi-Input, Multiple-Output (“MIMO”)communication system employs multiple transmit antennas per user andmultiple receive antennas for data transmission.

MUD refers to a receiver design technology for detecting desiredsignal(s) from interference and noise. A MUD receiver jointlydemodulates co-channel interfering (colliding) signals. In this regard,the MUD receiver may employ a maximum likelihood MUD technique or aTurbo MUD technique. The term “Turbo”, as used herein, refers to aniterative process for extracting data from receive samples. Turbo MUD istypically used by a MUD receiver to successfully recover the data of allcolliding co-channel signals. In Turbo MUD scenarios, processing isaccomplished by ping-ponging between two independent stages separated byan interleaver/de-interleaver to randomize burst error events from eachstage. This overall process is referred to herein as Turbo MUDprocessing, as mentioned earlier.

SUMMARY OF THE INVENTION

The invention concerns implementing systems and methods for receiveprocessing of a burst communication system where a plurality ofco-channels signals collide in a receiver. An example three co-channelsignal case is considered for sake of explanation where two of theco-channel signals may be of a similar power level and the third may beof a weaker power level such that it cannot be immediately discovered.The present invention supports more general cases. The co-channelsignals are transmitted from a plurality of remote transmitters at afirst frequency. The methods involve simultaneously receiving at least aportion of the co-channel signals; detecting each of a first co-channelsignal and a second co-channel signal by correlating a pre-amble and apost-amble thereof; and independently performing a first iteration of aTurbo MUD process for a first co-channel signal and a second co-channelsignal. In some scenarios, the pre-amble and post-amble of each firstand second co-channel signal are used to estimate at least one of anamplitude, a carrier phase, a frequency offset, and a fine timingoffset. One or more of the listed parameters can be used in the TurboMUD process.

The Turbo MUD process involves: segmenting each of the first and secondco-channel signals into a plurality of segments having unique Signal toInterference plus Noise Ratios; computing a noise variance estimate foreach segment; computing first bit likelihood values for each segmentbased on the noise variance estimate; computing second bit likelihoodvalues for each segment based on the first bit likelihood values (i.e.,soft-in soft-out); and using the second bit likelihood values togenerate a first estimate of the first and second co-channel signals.The first estimate can include a soft signal estimate without gain andcarrier phase adjustments.

Notably, during each iteration of the Turbo MUD process a matched filteris designed for each of the first and second co-channel signals usingthe estimate of the fine timing offset, respectively. Also, during asecond iteration of the Turbo MUD process, best estimates of the firstand second co-channel signals are subtracted from a combined co-channelsignal such that a third co-channel signal can be detected which has asignal power weaker than a signal power of the first and secondco-channel signals. Thereafter, Turbo MUD processing is independentlyperformed for the third co-channel signal. Additionally, prior to thesecond iteration of the Turbo MUD process for the first co-channelsignal, interference caused by the second co-channel signal to the firstco-channel signal is canceled. Similarly, prior to the second iterationof the Turbo MUD process for the second co-channel signal, interferencecaused by the first co-channel signal to the second co-channel signal iscanceled.

The Turbo MUD process further involves: using the first estimate tojointly estimate an amplitude and a carrier phase of the first andsecond co-channel signals; modifying the first estimate to produce asecond estimate with the jointly estimated amplitude and carrier phase;and using the second estimate in a subsequent iteration of the Turbo MUDprocess for amble correlation and interference cancellation.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments will be described with reference to the following drawingfigures, in which like numerals represent like items throughout thefigures, and in which:

FIG. 1 is a schematic illustration of an exemplary communication systemthat is useful for understanding the present invention.

FIG. 2 is a more detailed block diagram of the communication systemshown in FIG. 1.

FIG. 3 is a more detailed schematic illustration of an exemplaryarchitecture for transmitter shown in FIG. 2.

FIG. 4 is a perspective of a waveform when received by a receiver of thereceiving device shown in FIG. 2.

FIG. 5 is a schematic illustration of an exemplary Line-Of-Sight (“LOS”)channel model for a channel of FIG. 2.

FIG. 6 is a schematic illustration that is useful for understanding howan amplitude and phase of a waveform is estimated by a receiver using apre-amble and a post-amble

FIG. 7 is a schematic illustration that is useful for understanding howa frequency offset of a waveform is estimated by a receiver using apre-amble and a post-amble.

FIGS. 8-9 provide schematic illustrations that are useful forunderstanding how a time offset of a waveform is estimated by a receiverusing a pre-amble and post-amble.

FIG. 10 is a detailed block diagram that is useful for understanding howestimated parameters are used by the receiver when it is receiving onlyone signal during a given period of time.

FIG. 11 is a graph showing the distribution of noisy receive samplesabout ideal constellation points at an output of a matched filter.

FIG. 12 is a graph showing that received signals are detected on a realaxis for modulation techniques in which there is one coded bit persymbol.

FIG. 13 is a graph showing that received signals are detected on animaginary axis and a real axis for modulation techniques in which thereare two coded bits per symbol.

FIG. 14 is a block diagram of an exemplary transmitter employingfrequency hop technology.

FIG. 15 is a schematic illustration of an exemplary code frame (i.e.,transmit packet) output from the transmitter of FIG. 14.

FIG. 16 is a block diagram of a receiver employing frequency de-hoppingtechnology.

FIG. 17 is a schematic illustration of a multi-user channel model thatis useful for understanding the present invention.

FIG. 18 is a schematic illustration which is useful for understanding afrequency hopped multi-user application.

FIG. 19 is a schematic illustration that is useful for understandingreceiver multi-signal detection with initial user timing, amplitude,carrier phase and frequency offset.

FIG. 20 is a schematic illustration that is useful for understanding theTurbo MUD processing strategy for colliding co-channel signals.

FIG. 21 is a schematic illustration that is useful for understandingTurbo MUD processing using dynamical Signal to Interference plus NoiseRatio (“SINR”) segments.

FIG. 22 is a block diagram of an exemplary architecture for a receiverperforming a first pass of a Turbo MUD process in accordance with thepresent invention.

FIG. 23 is a block diagram of an exemplary architecture for a receiverperforming a subsequent pass of a Turbo MUD process in accordance withthe present invention.

FIG. 24 is a schematic illustration that is useful in understanding whathappens when a receiver successfully recovers the bits of a detectedco-channels signal.

FIG. 25 is a block diagram of an exemplary demodulator.

FIG. 26 is a block diagram that is useful for understanding how a bitlikelihood determination is made by the demodulator of FIG. 25.

FIG. 27 is a block diagram that is useful for understanding how softsignal estimates are generated by a signal reconstructor of a Signal OfInterest (“SOT”) Rx processing card when a successful CRC check has notyet occurred.

FIG. 28 is a block diagram that is useful for understanding how signalestimates are generated by a signal reconstructor of an SOT Rxprocessing card when a successful CRC check has occurred.

FIG. 29 is a graph plotting soft bit expected values versus loglikelihood ratios.

FIGS. 30-31 provide schematic illustrations that are useful forunderstanding joint amplitude and carrier phase estimation operationsperformed by a joint signal reconstructor of a Turbo MUD processor.

FIGS. 32-33 provide schematic illustrations that are useful forunderstanding how soft symbols (bits) can be used for soft modulation ofa single reconstructor.

FIG. 34 is a block diagram that is useful for understanding thecorrelation operations performed in a receiver.

FIG. 35 provides a flow diagram of an exemplary method for receiveprocessing of a burst communication system where a plurality ofco-channels signals collide in a receiver.

FIG. 36 provides a flow diagram of an exemplary Turbo MUD process.

DETAILED DESCRIPTION

It will be readily understood that the components of the embodiments asgenerally described herein and illustrated in the appended figures couldbe arranged and designed in a wide variety of different configurations.Thus, the following more detailed description of various embodiments, asrepresented in the figures, is not intended to limit the scope of thepresent disclosure, but is merely representative of various embodiments.While the various aspects of the embodiments are presented in drawings,the drawings are not necessarily drawn to scale unless specificallyindicated.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects as illustrative. Thescope of the invention is, therefore, indicated by the appended claims.All changes which come within the meaning and range of equivalency ofthe claims are to be embraced within their scope.

Reference throughout this specification to features, advantages, orsimilar language does not imply that all of the features and advantagesthat may be realized with the present invention should be or are in anysingle embodiment of the invention. Rather, language referring to thefeatures and advantages is understood to mean that a specific feature,advantage, or characteristic described in connection with an embodimentis included in at least one embodiment of the present invention. Thus,discussions of the features and advantages, and similar language,throughout the specification may, but do not necessarily, refer to thesame embodiment.

Furthermore, the described features, advantages and characteristics ofthe invention may be combined in any suitable manner in one or moreembodiments. One skilled in the relevant art will recognize, in light ofthe description herein, that the invention can be practiced without oneor more of the specific features or advantages of a particularembodiment. In other instances, additional features and advantages maybe recognized in certain embodiments that may not be present in allembodiments of the invention.

Reference throughout this specification to “one embodiment”, “anembodiment”, or similar language means that a particular feature,structure, or characteristic described in connection with the indicatedembodiment is included in at least one embodiment of the presentinvention. Thus, the phrases “in one embodiment”, “in an embodiment”,and similar language throughout this specification may, but do notnecessarily, all refer to the same embodiment.

As used in this document, the singular form “a”, “an”, and “the” includeplural references unless the context clearly dictates otherwise. Unlessdefined otherwise, all technical and scientific terms used herein havethe same meanings as commonly understood by one of ordinary skill in theart. As used in this document, the term “comprising” means “including,but not limited to”.

The present document generally describes a SISO physical layer linkstructure and the associated receive processing for a burstcommunication system where multiple signals collide in a receiver. Theterm “physical layer”, as used herein, refers to a waveform, a structureof the waveform, how a transmitter communicates the waveform from pointA to point B, and how the waveform is processed by a receiver. Thesignals can include, but are not limited to, signals communicated overLOS links.

Notably, signal collision is not prevented in the present systems usinglink negotiation. The term “link negotiation”, as used herein, refers tomechanisms for allowing only one transmitter to be received on aparticular channel at any given time. Such mechanisms include, but arenot limited to, hardware and/or software configured to assign one ormore timeslots during which a single transmitting communication devicecan transmit data in a network and during which receiving communicationdevices listen for communications from the transmitting device.

Instead of “link negotiation”, the present invention uses Turbo MUDprocessing methods to successfully receive the data of all collidingco-channel signals with a relatively high degree of success. The term“co-channel signals”, as used herein, refers to two or more signalstransmitted from two or more transmitters at the same frequency. TheTurbo MUD processing methods will be described in detail below. Still,it should be understood that the Turbo MUD processing methods assumethat the receiver does not know in advance the following parameters: howmany signals are in a collision cluster; and the timing, amplitude,carrier phase, and/or frequency offset of the signals in the collisioncluster. These unknown parameters are estimated by a receiver, as willbecome more evident as the discussion progresses.

Exemplary System Architecture and Transmit Signal Description

Referring now to FIG. 1, there is provided a schematic illustration ofan exemplary communication system 100 that is useful for understandingthe present invention. The communication system 100 is an ad hoc systemcomprising a plurality of mobile transmitting devices 104-112 and amobile receiving device 102. The mobile transmitting devices 104-112have a single transmit antenna 152. Similarly, the mobile receivingdevice 102 has a single receive antenna 150. As such, the communicationsystem 100 is a SISO communication system. Notably, each of the devices102-112 can have at least one electronic circuit configured to performone or more of the methods described below.

The transmitting devices 104-112 communicate with the receiving device102 via communication links 120-128, respectfully. The communicationlinks 120-128 include, but are not limited to, LOS links. Thetransmitting devices 104-112 can dynamically enter and exit a receivingdevice's range. As such, networks of users dynamically coalesce and thendissolve. Also, two or more of the transmitting devices 104-112 maytransmit signals simultaneously to the receiving device 102. In suchscenarios, signal collision at the receiving device 102 occurs.

Referring now to FIG. 2, there is provided a more detailed block diagramof the communication system 100 shown in FIG. 1. As shown in FIG. 2,each transmitting device 104-112 comprises a transmitter 202-210 fortransmitting signals at the same frequency via a channel 212-220 to thereceiving device 102, respectively. An exemplary architecture fortransmitters 202-210 will be discussed below in relation to FIG. 3. Thechannels 212-220 comprise, but are not limited to, a plurality ofdifferent LOS channels.

At any given time, signals transmitted from two or more transmittingdevices 104-112 at the same frequency can be simultaneously received byreceive antenna 150. The simultaneously received signals are alsoreferred to herein as “colliding co-channel signals”. At the receiveantenna 150, the colliding co-channels signals are combined together(i.e., added) to form a single combined signal which is passed to frontend circuit 250 of the receiving device 102.

Front end circuits of receivers are well known in the art, and thereforewill not be described in detail herein. Still, it should be understoodthat the front end circuit 250 down converts, filters and samples thecombined signal. This type of filtering can be performed using ananti-alias filter. The samples are analog samples that are subsequentlyconverted to digital samples. The sampling can be achieved using anAnalog-to-Digital Converter (“ADC”). The digital samples are thenforwarded from the front end circuit 250 to the soft-in soft-out MUDdetector 224, such that Turbo MUD processing can be performed thereon.Anti-alias filters and ADC converters are well known in the art. Anyknown or to be known anti-alias filter and ADC converter can be usedherein without limitation.

The soft-in soft-out MUD detector 224 and components 226-230collectively provide a device for converting received signals from theirtransmitted form (e.g., a Phase Shift Keying (“PSK”) format or a MinimumShift Keying (“MSK”) format) into a form (e.g., a binary format)interpretable to other electronic components of the receiving device102. In this regard, the soft-in soft-out MUD detector 224 and soft-insoft-out FEC decoder 228 ping-pong information back and forth until thereceiver 222 determines that it successfully received one of thecolliding co-channels signals of interest, or times out. The soft-insoft-out MUD detector 224 and soft-in soft-out FEC decoder 228 will bedescribed in detail below. Still, it should be understood that thesoft-in soft-out MUD detector 224 generally computes interferenceestimates, computes bit and symbol likelihood values, and performsinterference cancellation operations. The soft-in soft-out FEC decoder228 generally employs an FEC technique to mitigate bit errors in thesignal being processed.

Notably, an interleaver 230 and a de-interleaver 226 reside between thesoft-in soft-out MUD detector 224 and soft-in soft-out FEC decoder 228.Interleavers and de-interleavers are well known in the art, andtherefore will not be described in detail herein. Still, it should beunderstood that these components 226, 230 are provided to improve theFEC technique employed by the soft-in soft-out FEC decoder 228. In thisregard, errors in a colliding co-channel signal may occur in burstsrather than independently. If the number of errors within a code wordexceeds the FEC code's capability, then the soft-in soft-out FEC decoder228 fails to recover the original word. Interleaving ameliorates thisproblem by shuffling source bits, thereby creating a more uniformdistribution of errors. Any known or to be known interleaver andde-interleaver architecture can be used with the present inventionwithout limitation.

Referring now to FIG. 3, there is provided a more detailed schematicillustration of an exemplary architecture for transmitter 202 of FIG. 2.Each of the transmitters 204-210 are the same as or similar totransmitter 202. As such, the following discussion of transmitter 202 issufficient for understanding transmitters 204-210. Transmitter 202 caninclude more or less components that are shown in FIG. 3. Still, thearchitecture of FIG. 3 is sufficient for illustrating the manner inwhich a transmit packet (i.e., a code frame) of a co-channel signal isgenerated at a transmitter. Notably, transmitter 202 will be describedherein as employing a 1-to-2 bit per symbol modulation scheme, such as aBinary PSK (“BPSK”) digital modulation scheme, a Quadrature PSK (“QPSK”)digital modulation scheme or a Gaussian MSK (“GMSK”) digital modulationscheme. Embodiments of the present invention are not limited in thisregard. Alternatively, the transmitter 202 can employ higher levelmodulation schemes, such as an 8-PSK modulation scheme and a 16Quadrature Amplitude Modulation (QAM) modulation scheme.

Transmitter 202 is generally configured to convert a block of data bits302 to a waveform at some Radio Frequency (“RF”). In this regard,transmitter 202 comprises a Cyclic Redundancy Check (“CRC”) appender304, an FEC encoder 306, an interleaver 310, an amble appender 312, anda modulator 314. The CRC appender 304 employs a CRC technique for addingCRC bits to the block of data bits 302. CRC techniques are well known inthe art, and therefore will not be described herein. Still, it should beunderstood that the CRC bits are used by receiving device 102 todetermine if it has successfully received the block of data bits 302.Any known or to be known CRC technique can be implemented herein withoutlimitation. For example, a block 302 comprises one hundred data bits.CRC bits are added to the block of data bits 302 for purposes ofproviding a mathematical framework for error detection at the receivingdevice 102. At the receiving device 102, the CRC appended block of databits is processed in the context of the mathematical framework providedby the CRC code. Based on this processing, the receiving device 102determines if one or more errors most likely exist in the respectivedemodulated signal of interest within the colliding co-channel signal.Embodiments of the present invention are not limited to theparticularities of this example.

After appending the CRC bit(s) to the block of data bits 302, the FECencoder 306 adds FEC bits to the output of the CRC appender 304 so as toform a block of code bits 308. In some scenarios, one or two extra FECbits are added for every data bit of block 302. The FEC bits generallyallow the receiving device 102 to successfully receive the block of databits 302 transmitted over an unreliable or noisy channel. Moreparticularly, the FEC bits allow the receiving device 102 to detect alimited number of errors that may occur anywhere in the transmittedblock of data bits, and often to correct these errors withoutretransmission. The FEC encoder 306 can employ any known or to be knownFEC technique that allows the use of a peer soft-in soft-out FEC decoderin the receiver that takes in and outputs log likelihood ratios orapproximations thereof.

The block of code bits 308 are then communicated from the FEC encoder306 to the interleaver 310. The interleaver 310 allows the receivingdevice 102 to disperse burst errors, as described above. Subsequently,at the ample appender 312, a pre-amble and a post-amble are appended tothe output of the interleaver 310. Pre-ambles and post-ambles are wellknown in the art, and therefore will not be described in detail herein.Still, it should be understood that the pre-amble comprises a fixedpattern for providing an indication to the receiving device 102 of thestart of a co-channel signal. The post-amble comprises a fixed patternproviding an indication to the receiving device 102 of the end of aco-channel signal.

The output 316 of the amble appender 312 is then communicated to themodulator 314. The modulator 314 employs a digital modulation schemethat conveys the data 316 by changing, or modulating, the amplitude,frequency, and/or phase of a reference signal. Digital modulationschemes are well known in the art, and therefore will not be describedherein. Such digital modulation schemes include, but are not limited to,BPSK, QPSK and GMSK. The output of the modulator 314 is referred to as atransmit packet (i.e., code frame) 318.

A schematic illustration of the transmit packet (i.e., code frame) 318is provided in FIG. 4. As shown in FIG. 4, the transmit packet 318comprises a pre-ample 402, data payload 404, and a post-amble 406. Thedata payload 404 includes the CRC bits, FEC bits, block of data bits 302and headers/trailers of protocol stack layers (not shown). Headers andtrailers are well known in the art, and therefore will not be describedherein. The data payload 404 is the portion of the transmit packet 318that is to be recovered by the receiver 222 of the receiving device 102.

FIG. 4 also shows a perspective of a waveform when received by receiver222 of receiving device 102. As can be seen in FIG. 4, the receiver 222first detects noise. Shortly thereafter, the receiver 222 detects theon-set of the pre-amble 402 of the waveform at a start time 410. Atstart time 410, the receiver 222 detects a pre-amble 402, therebydetermining that a signal is starting. The incoming waveform has acertain amplitude 416 above the noise floor 408 and a duration 418. Theduration 418 begins at start time 410 and ends at stop time 412. Thepost-amble 406 allows the receiver 222 to detect the stop time 412 ofthe waveform, i.e., when the signal is ending.

Referring now to FIG. 5, there is provided a schematic illustration ofan exemplary LOS channel model 500 for channel 212. Channels 214-220 arethe same as or similar to channel 212. As such, the following discussionof channel 212 is sufficient for understanding channels 214-220. Themodel 500 is assumed to only impose a time delay, an amplitude changeand a carrier phase shift to the co-channel signal. A frequency offsetcan exist between the transmitting device 202 and the receiving device102. The frequency offset can result from: oscillator mismatch betweenthe transmitter 202 and receiver 222; and/or Doppler offset due torelative movement between the transmitter 202 and receiver 222. Thelisted parameters (i.e., amplitude, carrier phase, frequency offset, andtiming) are assumed to be essentially constant over the transmit packet(i.e., code frame). The receiver 222 estimates the above-listedparameters for every transmit packet in each colliding co-channelsignal, as will be discussed below.

Single User Receiver with Parameter Estimation Description

The amplitude and carrier phase of a waveform is estimated by thereceiver 222 using a correlation technique. Correlation techniques arewell known in the art, and therefore will not be described herein.Still, it should be understood that the correlation technique employedby receiver 222 is used to correlate for the pre-amble 402 andpost-amble 406. The ambles 402, 406 comprise sync patterns with knownwaveform shapes. The ambles 402, 406 also have impulsive correlationproperties and a known separation in time. Once the known waveform shapeof the pre-amble or post-amble is detected, the receiver 222 performsoperations to determine the location of the correlation peak of theambles. As shown in FIG. 6, impulse 602 identifies the location in thepre-amble 402 of the correlation peak 606. Similarly, impulse 604identifies the location in the post-amble 406 of the correlation peak606. The correlation peaks 606 provide estimates of the amplitude andcarrier phase of the waveform at particular times.

The frequency offset of a waveform is also estimated by the receiver 222using the pre-amble 402 and post-amble 406. If there is a frequencyoffset, then the signal's phase is spinning in a real and imaginaryplane due to the fact that there is a relative offset in the frequencybetween the transmitter 202 and receiver 222. The phase rotationobserved over a transmit packet (i.e., code frame) is proportional tothe frequency offset of the waveform, assuming that the frequency offsetis small enough that the phase rotation from the pre-amble to thepost-amble is sufficiently less than ±180 degrees. Accordingly, bylooking at how the phase changed between impulse 602 and impulse 604,the receiver 222 can compute an estimate of the frequency offset. Thefrequency offset estimate is defined by the following mathematicalequation (1).

f _(estimate)=(θ₂−θ₁)/2πT _(Δ)  (1)

where f_(estimate) represents the estimate of the frequency offset. θ₁represents a phase of a waveform when impulse 602 occurs. θ₂ representsthe phase of the waveform when impulse 604 occurs. T_(Δ) represents thetime period between the occurrence of impulse 602 and impulse 604.

The timing can also be estimated by the receiver 222 using the pre-amble402 and post-amble 406. When the receiver 222 correlates, it detects thecorrelation peak 602 of the analog pre-amble 402 and analog post-amble406. The pre-amble digital samples output from the correlator straddlethe correlation peak of the analog pre-amble, as shown in FIG. 8, sincesampling is a discrete process. Similarly, the post-amble digitalsamples straddle the correlation peak of the analog post-amble. FIG. 8is a notional diagram to illustrate that the analog correlation peak 606is between the two digital samples 802 and 804. By looking at thepre-amble digital samples which straddle the correlation peak of theanalog pre-amble and the post-amble digital samples which straddle thecorrelation peak of the analog post-amble, the receiver 222 can resolvefine timing, i.e., determine exactly where the true correlation peak ofthe analog pre-amble or analog post-amble is relative to two digitalsamples 802, 804. The location of the true collection peak is then usedto compute the fine timing offset between the incoming signal and thereceive sampling. The fine timing offset is then used by the receiver222 to identify or design a matched filter 902 required for the incomingsignal.

The matched filter 902 of FIG. 9 generally compensates for any finetiming offset, so at the output the correlation peak occurs on sample,and all receiver symbols are sampled optimally. More particularly, thematched filter 902 of FIG. 9 maximizes the Signal-to-Noise Ratio (“SNR”)of the digital samples and aligns the post match-filtered correlationpeak of the digital sample stream with the sample timing. As a result ofsuch alignment, the amplitude peak of the pre-amble or post-amble postmatched-filter digital samples is maximized and optimized for mid-symboltiming. Notably, in the multi-user case a matched filter will beidentified or designed for each incoming colliding co-channel signal, asexplained below.

Referring now to FIG. 10, there is provided a detailed block diagramthat is useful for understanding how the estimated parameters are usedby a receiver 1000 when it is receiving only one signal during a givenperiod of time. As shown in FIG. 10, the front end circuit 1050comprises an anti-alias filter 1002 and a sampler 1004. The samples 1005output from the sampler 1004 are then passed to a first stage 1060 of aTurbo MUD process.

During the first stage 1060, the samples 1005 are used by the amblecorrelator 1008 to correlate a pre-amble and a post-amble. The resultsof the correlation are then used by the parameter estimator 1010 todetermine estimates of various parameters. The parameters include, butare not limited to, the amplitude, carrier phase, timing and frequencyoffset. These parameters are determined in the manner described above inrelation to FIGS. 6-7. The estimated frequency offset in the signal isremoved by component 1006. Also, the carrier phase of the signal iscorrected by component 1006. The output of component 1006 is thencommunicated to the matched filter 1009. The matched filter 1009maximizes the SNR so as to produce symbol samples 1011 aligned withcorrelation peaks of the post match-filtered signal.

The symbol samples 1011 are used by the noise power determiner 1012 tocompute an estimate of noise power or variance. The noise power orvariance is defined by the following mathematical equation (2).

σ² _(n)σ² _(r)+σ² _(l)  (2)

for complex Gaussian noise where typically θ² _(r)=σ² _(l) and σ²_(n)=σ² _(r), for real Gaussian noise (i.e., σ² _(l)=0). To estimate thenoise power or variance, the noise power determiner 1012 measures thenoisy receive sample distribution about ideal constellation points atthe output of the matched filter 1009 (best timing, frequency offsetremoved, carrier phase corrected, and amplitude compensated for relevantmodulations).

A QPSK example sample distribution of noisy receive samples is shown inthe graph 1100 of FIG. 11 for a 10 dB SNR case. Graph 1100 comprisesvalues 1102 for ideal samples and values 1104 for a plurality of noisyreceived samples output from matched filter 1009. To estimate the noisepower or variance, the noise power determiner 1012 can: (1) subtract thepower of the ideal samples from the total power of the noisy receivesample; (2) average a squared distance of the noisy receive samples fromthe corresponding closest ideal sample; or (3) compute a maximumlikelihood noise power estimate using standard methods.

Notably, interference from other signals act similar to thermal noise,causing the receive samples to scatter in the plot of FIG. 11. While theinterference is not Gaussian, the receiver 1000 makes the assumptionthat it is for bit and symbol likelihood computation. On subsequentTurbo MUD processing iterations, the interference will be at leastpartially canceled. During Turbo MUD processing, there will be errors inthe parameter estimates for each signal. This will increase thenoisiness of the receive sample scatter graph 1100, increasing the noisepower estimate. This works well because the bit and symbol likelihoodswill automatically be degraded (become less confident) in a gracefulmanner when parameter estimates are less accurate. After each Turbo MUDprocessing iteration, the parameter estimates tend to become moreaccurate.

Referring again to FIG. 10, the noise power or variance estimate is thenprovided to the bit likelihood estimator 1014. The bit likelihoodestimator 1014 uses the noise power and optimal theory to determine hownoisy each symbol sample 1011 is and computes a first bit likelihoodvalue estimating an accuracy of the bit value(s) for each symbol sample1011.

If a BPSK or GSM like GMSK modulation scheme is employed, then one codedbit is represented by each complex symbol. GSM like GMSK modulationschemes are well known and understood by those skilled in the art, andtherefore will not be described herein. The real component of thematched filter output complex symbol represents the coded bit. In thisscenario, the first bit likelihood value is defined by the followingmathematical equation (3), which is optimal in probability theory forassigning a confidence level to data in noise.

$\begin{matrix}{{{LLR}\left( {x/b} \right)} = {{\log \left\{ \frac{P\left( {{x/b} = {+ 1}} \right)}{P\left( {{x/b} = {- 1}} \right)} \right\}} = {{{- \frac{\left( {x - A} \right)^{2}}{\sigma_{r}^{2}}} + \frac{\left( {x - A} \right)^{2}}{\sigma_{r}^{2}}} = \frac{2{Ax}}{\sigma_{r}^{2}}}}} & (3)\end{matrix}$

where LLR (x/b) represents the first bit likelihood value. σ² _(r)represents the noise power of a real component of a noisy receivedcomplex sample. x represents a value of a real part 1202 of a noisyreceived complex sample, as shown in FIG. 12. A represents an amplitudevalue 1204 of a noise free symbol point 1204 as also shown in FIG. 12.For an ideal noise free link, the amplitude of the received symbolswould lie on or be equal to ±A, corresponding to a ±1 code bit symbol,in turn corresponding for example to a bit with a value of 1 or 0. Thenoise power causes the amplitude of the receive symbols to deviate fromthe ideal points or values ±A.

In contrast if a QPSK modulation scheme is employed, then two coded bitsare represented by each complex symbol. The imaginary component of thecomplex symbol represents a first coded bit, while the real component ofthe complex symbol represents a second coded bit. In this scenario, thefirst likelihood value is defined by the following mathematicalequations (4) and (5).

$\begin{matrix}{{{Real}\mspace{14mu} {code}\mspace{14mu} {bit}\text{:}\mspace{14mu} {{LLR}_{EXT}\left( {x_{r}/b} \right)}} = {{\log \left\{ \frac{P\left( {{x_{r}/b} = {+ 1}} \right)}{P\left( {{x_{r}/b} = {- 1}} \right)} \right\}} = {{{- \frac{\left( {x_{r} - A} \right)^{2}}{\sigma_{r}^{2}}} + \frac{\left( {x_{r} - A} \right)^{2}}{\sigma_{r}^{2}}} = \frac{2{Ax}_{r}}{\sigma_{r}^{2}}}}} & (4) \\{{{Imag}\mspace{14mu} {code}\mspace{14mu} {bit}\text{:}\mspace{14mu} {{LLR}_{EXT}\left( {x_{i}/b} \right)}} = {{\log \left\{ \frac{P\left( {{x_{i}/b} = {+ 1}} \right)}{P\left( {{x_{i}/b} = {- 1}} \right)} \right\}} = {{{- \frac{\left( {x_{i} - A} \right)^{2}}{\sigma_{i}^{2}}} + \frac{\left( {x_{i} - A} \right)^{2}}{\sigma_{i}^{2}}} = \frac{2{Ax}_{i}}{\sigma_{i}^{2}}}}} & (5)\end{matrix}$

where x_(i) represents a value 1304 of an imaginary component of a noisyreceived complex sample, as shown in FIG. 13. x_(r) represents a value1302 of a real component of a noisy received complex sample, as alsoshown in FIG. 13. σ² _(i) represents the noise power of an imaginarycomponent of a noisy received complex sample. σ² _(r) represents thenoise power of a real component of a noisy received complex sample. Formost cases, the real and imaginary noise variances are equal, so σ²_(r)=σ² _(i). For an ideal noise free link, the received symbols wouldlie on ±A, corresponding to a ±1 code bit symbol, in turn correspondingfor example to a bit with a value of 1 or 0. The noise power causes thereceive signal to deviate from the ideal points ±A. Notably, the noiseon the real axis is statistically independent of the noise on theimaginary axis.

Once the first bit likelihood values are estimated, they arecommunicated to the second stage of the Turbo MUD process. The secondstage comprises an FEC decoder 1018. The FEC decoder 1018 uses the firstbit likelihood values to generate a new and improved set of bitlikelihood values (i.e., soft-in soft-out). The bit likelihood valuesoutput from the FEC decoder 1018 are referred to herein as second bitlikelihood values.

As can be seen in FIG. 10, a de-interleaver 1016 is provided between thefirst and second stages 1060, 1062 of the Turbo MUD process. Thede-interleaver 1016 is provided to improve the FEC technique employed bythe FEC decoder 1018. In this regard, errors in an incoming signaltypically occur in bursts rather than independently. If the number oferrors within a code word exceeds the FEC code's capability, then theFEC decoder 1018 fails to recover the original word. Interleavingameliorates this problem by shuffling source bits, thereby creating amore uniform distribution of errors. Any known or to be knownde-interleaver architecture can be used with the present inventionwithout limitation.

The output of the FEC decoder 1018 is passed to a CRC checker 1020. TheCRC checker 1020 determines whether samples were decoded correctly. CRCtechniques for making such a determination are well known in the art,and therefore will not be described herein. Any known or to be known CRCtechnique can be used with the present invention without limitation.

Single User Frequency Hopped Description

Referring now to FIG. 14, there is provided a block diagram of anexemplary transmitter 1400 employing frequency hopping technology. Thetransmitter 1400 can be used in frequency hopped single user transmitapplications. Notably, the transmitter 1400 has an architecture similarto that of the transmitter shown in FIG. 3. In this regard, thetransmitter 1400 comprises a CRC appender 1404, an FEC encoder 1406, aninterleaver 1410, an amble appender 1414, and a modulator 1416. Each ofthese components 1404-1410, 1414, 1416 is the same as or similar to therespective component 304, 306, 310-314 of FIG. 3. Therefore thediscussion above in relation to components 304, 306, 310-314 issufficient for understanding components 1404-1410, 1414, 1416. Still, itshould be understood that the interleaver 1410 spans the whole codeblock which spans all the hops in a transmit packet (i.e., code frame).

As shown in FIG. 14, the transmitter 1400 includes two additionalcomponents 1412 and 1418. Component 1412 is a hop block generatorconfigured to subdivide an interleaved block of coded bits 1411 into Nhop blocks, where N is an integer. Ambles are appended to each hop blockby amble appender 1414 so as to form a plurality of packet segments.Component 1418 is a frequency hop synthesizer configured to generate acode frame 1420, wherein each segment of a transmit packet (i.e., codeframe) is transmitted at a different pre-defined frequency. Hop blockgenerators and frequency hop synthesizers are well known in the art, andtherefore will not be described in more detail herein. Any known or tobe known hop block generator and/or frequency hop synthesizer can beused herein without limitation.

A schematic illustration of code frame 1420 (i.e., transmit packet) isprovided in FIG. 15. As shown in FIG. 15, the code frame 1420 comprisesa plurality of packet segments 1502, 1504, 1506, 1508 arranged in aserial manner. Each packet segment 1502-1508 includes a pre-amble 1510,a data payload 1512, and a post-amble 1514. Each packet segment1502-1508 is transmitted at a different pre-defined frequency 1520-1526.

Referring now to FIG. 16, there is provided a block diagram of anexemplary receiver 1600 employing frequency de-hopping technology. Thereceiver 1600 can be used in frequency hopped single user receiveapplications. Notably, the receiver 1600 has an architecture similar tothat of the receiver shown in FIG. 10. In this regard, the receiver 1600comprises an anti-alias filter 1602, a sampler 1604, an amble correlator1608, a parameter estimator 1610, a frequency and phase offset remover1606, a matched filter 1609, a bit likelihood estimator 1614, ade-interleaver 1016, an FEC decoder 1018, and a CRC checker 1020. Eachof these listed components 1602-1620 is the same as or similar to arespective component 1002, 1004, 1006-1010, 1012, 1014-1020 of FIG. 10.The description of components 1002, 1004, 1006-1010, 1012, 1014-1020provided in relation to FIG. 10 is sufficient for understandingcomponents 1602-1620.

As shown in FIG. 16, receiver 1600 comprises an additional component1601. Component 1601 is a frequency de-hop synthesizer. Frequency de-hopsynthesizers are well known in the art, and therefore will not bedescribed herein. Any known or to be known frequency de-hop synthesizercan be used herein without limitation.

During operation, the receiver 1600 correlates for the ambles of eachpacket segment and performs user detection (signal discovery) byobserving all frame hops or less than all frame hops. Following signaldiscovery, signal parameter estimation can ensue. Notably, nominalreceived signal timing-offset relative to a hop boundary is assumedconstant, to within a symbol period. The frequency offset is assumedconstant across all hops to within a Part Per Million (“PPM”) parameter.Hence, the frequency offset can be estimated using all hops. All otherparameters may be independently estimated in each hop. These parametersinclude, but are not limited to, timing offset, carrier phase, andamplitude. It should also be noted that the matched filter varies fromhop to hop due to fine timing offsets.

Multi-User Transmit Signal Description

Referring now to FIG. 17, there is provided a schematic illustration ofa multi-user channel model 1700 that is useful for understanding thepresent invention. As shown in FIG. 17, the channel model 1700 comprisestransmitters 1702-1706 and channels 1708-1712 as an illustrative examplefor the sake of explanation. The channel model 1700 also comprises anantenna element 1714, and a receiver 1716. The transmitters 1702-1706transmit signals 1720-1726 at the same frequency over channels1708-1712, respectively. These signals are referred to herein asco-channel signals. The co-channel signals 1720-1726 are combinedtogether at antenna element 1714 to form a combined co-channel signal.The combined co-channel signal is then forwarded to the receiver 1716for Turbo MUD processing. In order to successfully perform Turbo MUDprocessing of each co-channel signal 1720-1726, the receiver 1716 mustdetect each co-channel signal 1720-1726 within the combined co-channelsignal, and separate the co-channel signals 1720-1726.

As shown in FIG. 17, the co-channel signals 1720-1726 arrive at thereceiver 1716 with random relative offsets in time, amplitude, carrierphase and frequency PPM. As such, the co-channel signals 1720-1726 forthe users are staggered in time and amplitude. Each co-channel signal1720-1726 can also have its own carrier phase and frequency offset. Theuniqueness in time, amplitude and frequency offset of each user allowsthe receiver 1716 to detect and separate the co-channel signals1720-1726.

At the receiver 1716, the correlation operations are performed using thepre-ambles and post-ambles of the co-channel signals 1720-1726. As aresult of the correlation operations, the receiver 1716 detects(discovers) the presence of each co-channel signal 1720-1726 in thecombined co-channel signal received by antenna element 1714. Afterdetecting a co-channel signal, the receiver 1716 begins a Turbo MUDprocess for decoding the co-channel signal. Each co-channel signal isprocessed independently, as will be described below. The pre-amble andpost-amble correlation operations provide a mechanism for the receiver1716 to detect (discover) the number of co-channel signals for theinitial Turbo MUD processing.

In some scenarios, the RF signal power of a co-channel signal 1726 isless than co-channel signals 1720 and 1724 by a relatively large amount.Consequently, the receiver 1716 does not detect (discover) co-channelsignal 1726 during its first correlation operations. However, duringTurbo MUD processing, the receiver 1716 will subtract out the bestestimates of co-channels 1720 and 1724 from the combined co-channelsignal. The resulting signal is then analyzed by the receiver 1716 todetermine if any other co-channel signals are present in the combinedco-channel signal which was not previously detected (discovered). Thisdetermination can be made using pre-amble and post-amble correlationoperations, and can again be used to detect (discover) the number ofadditional co-channel signals, if any, to be included in the Turbo MUDprocessing. As a result of this analysis, the receiver 1716 can detectco-channel signal 1726 and begin performing a Turbo MUD process usingco-channel signal 1726.

In some scenarios, the co-channel signals comprise frequency hoppedco-channel signals, as shown in FIG. 18. The interference scenario ofthe hops for all users, in terms of the relative signal timing andamplitude, is relatively constant. Moreover, all user's code frames(i.e., transmit packets) are time aligned over the interferencescenario. With this variant, the transmit packet (code frame) of eachco-channel signal is spread across multiple frequency hops where theinterference pattern is essentially the same in each hop. Each hop hasappended ambles. The relative amplitudes, time offsets and frequencyoffsets may be nominally constant from hop to hop, or not. So, theseparameters may be either jointly estimated or individually estimatedacross all hops in a code frame. The received carrier phase is assumedrandom for each hop frequency, hence it must be individually estimatedacross all hops in a code frame. User detection may occur by observingall packet hops if desired.

Multi-User Receiver with Parameter Estimation Description

Many wireless communication systems use a two step communicationprocess. A base station registers with a receiver and then negotiatescapabilities and preferred communication modes. Then, the datacommunication commences using the agreed upon communication mode. Thistype of system tends to have more latency in data transfer than in thepresent communication systems.

The context here is blind burst communications where the receiver doesnot know in advance if or when a data packet will arrive. So, the signalmust be detected and processed from a single data packet. Also, multipleuser signals may arrive simultaneously as co-channel interference. Thegoal is to successfully receive all the user data. The present method ofcommunication has less latency then that described above in which linknegotiation is employed.

Referring now to FIG. 19, there is provided a schematic illustrationthat is useful for understanding receiver multi-signal detection usingvarious parameters. The parameters include, but are not limited to,timing, amplitude, carrier phase and frequency offset. At the receiver,an initial estimate of the interference scenario is provided by theamble correlation process. As shown in FIG. 19, even though the jointinterference is severe, the impulsive characteristic and the processinggain of the amble correlation allows multiple users to be identified ona single pass with initial estimates for timing, amplitude, carrierphase and frequency offset. The Turbo MUD processing will then commenceusing the observed estimates. Note, if two users with the same amblesexactly collide with zero time offset and identical amplitude levels,the receiver will not be able to distinguish those signals. This isconsidered a catastrophic event. However, it is a low probability eventbecause both the timing and amplitude of two signals is rarely the same.

Referring now to FIG. 20, there is provided a schematic illustrationthat is useful for understanding a Turbo MUD processing strategy forcolliding co-channel signals. In the present invention, the Turbo MUDprocess is iterative. Therefore, it is not necessary to recover all theco-channel signals 2002 during a first iteration of the Turbo MUDprocess. It is only necessary to learn more about the signals duringeach iteration. Notably, parameter estimation and data estimationimprove each pass with the help of the FEC decoder coding gain andinterference cancellation. If needed, the Turbo MUD processing can belayered. The strongest co-channel signals 2002, 2004 can be detectedfirst. Then, the next weaker co-channel signal(s) 2006 can be detected.The layering is advantageous in these cases when the weaker signalscannot be discovered or properly detected until the stronger signals aredetected and subsequently excised from the composite signal. Theiterative and layered nature of the Turbo MUD processing strategy, alongwith the pre-amble and post-amble based signal discovery mechanism,allows for operation with a number of colliding co-channel signals witharbitrary power levels and timing offsets.

In the present invention, the Turbo MUD process employs iterativeinterference canceling. To recover a weaker signal 2006, the strongerco-channel signals 2002, 2004 must be subtracted from the combinedco-channel signal received at the receiver. The interference cancellingis soft, meaning interference is only partially removed when thereceiver is not confident of what the interference is. The confidencecan vary symbol by symbol. Symbol likelihood is a measure of symbolconfidence. Symbol likelihood is related to the bit likelihood valuesfor the bits that comprise the symbol according to the modulationscheme.

Referring now to FIG. 21, there is provided a schematic illustrationthat is useful for understanding a Turbo MUD processing using dynamicSignal to Interference plus Noise Ratio (“SINR”) segments. Notably, theTurbo MUD process described below in relation to FIG. 21 can beperformed across all hops in a frequency hop scenario.

As shown in FIG. 21, co-channel signal 2002 has three distinct segments2102, 2104, 2106. Segment 2106 is in the presence of thermal noise, butis not in collision with any co-channel signals. Segment 2104 is in thepresence of thermal noise and is in collision with co-channel signal2006. The receive signal power of co-channel signal 2006 is weakcompared to that of co-channel signal 2002. As such, co-channel signal2006 causes a relatively small amount of signal distortion to segment2104 of co-channel signal 2002. Similarly, segment 2002 is in thepresence of thermal noise and is in collision with co-channel signal2006. Co-channel signal 2006 causes a relatively small amount of signaldistortion to segment 2002. However, segment 2002 is also in collisionwith co-channel signal 2004. Since the RF signal power of co-channelsignals 2002 and 2004 are close in value, co-channel signal 2004 causesa relatively large amount of signal distortion to segment 2102 ofco-channel signal 2002.

In the present invention, the receiver detects the start and stop timesof each co-channel signal 2002, 2004, 2006. The receiver can use thesestart and stop times to determine the overlap conditions of theco-channel signals 2002, 2004, 2006. Accordingly, the receiver candivide each co-channel signal 2002, 2004, 2006 into a plurality ofsegments where the SINR is unique for each segment. Thereafter, thereceiver will perform bit likelihood estimations during its Turbo MUDprocessing of each co-channel signal 2002, 2004, 2006. The bitlikelihood estimations for each co-channel signal will be segmented. Inthis regard, the receiver will determine a noise and interference poweror variance estimate for each segment 2102, 2104, 2106.

Thereafter, all the bits in a given segment 2102, 2104, 2106 of theco-channel signal will have a bit likelihood estimate computed thereforeusing the respective noise and interference power or variance estimate.For example, a bit likelihood value for each bit of segment 2106 isdetermined using a first noise and interference power or varianceestimate. The bit likelihood values for these bits indicate a relativelyhigh confidence level since the segment 2106 is not in collision withanother co-channel signal. A bit likelihood value for each bit ofsegment 2104 is determined using a second noise power or varianceestimate. The bit likelihood values for these bits indicate a relativelylower confidence level since the segment 2104 is in collision withco-channel signal 2006. A bit likelihood value for each bit of segment2102 is then determined using a third noise power or variance estimate.The bit likelihood values for these bits indicate an even lowerconfidence level since segment 2102 is in collision with co-channelssignals 2004 and 2006.

Once the bit likelihood values have been computed, then the bits ofco-channel signal 2002 are sent to an FEC decoder via a de-interleaver.The bit likelihood values are also sent to the FEC decoder. The FECdecoder uses the first bit likelihood values to generate a new andimproved set of bit likelihood values (i.e., soft-in soft-out). Duringeach iteration of the Turbo MUD process, the receiver's confidence levelof each bit value usually increases since the previous estimate of otherco-channel signal(s) are subtracted out of a combined co-channel signalprior to a next iteration of the Turbo MUD process for the co-channelsignal of interest. As a result of the signal subtraction, there isusually less signal distortion experienced by segments 2102, 2104resulting from interference with other co-channel signals. The Turbo MUDprocessing treats each of the individual co-channel signal(s) thatcomprise the composite co-channel signal as the Signal Of Interest(“SOI”) in turn, with the other individual signals treated asinterfering signals, as processing unfolds.

In some scenarios, the signal subtraction is performed on a symbol bysymbol basis. For example, if the confidence level is relatively highfor a first symbol of a co-channel signal 2004, then the interferencecaused thereby to co-channel signal 2004 is removed. In contrast, if theconfidence level is relatively low for a second symbol of co-channelsignal 2004, then the interference caused thereby to co-channel signal2004 is not removed. As noted above, the bit (hence symbol) confidencelevels are usually improved during each iteration of the Turbo MUDprocess. Accordingly, signal interference is usually further reducedfrom the co-channel signal 2004 during each subsequent iteration of theTurbo MUD process.

Exemplary Multi-User Receiver Architecture

Referring now to FIG. 22, there is provided a block diagram of anexemplary architecture for a receiver 2200 performing a first pass of aTurbo MUD process in accordance with the present invention. As shown inFIG. 22, the receiver 2200 comprises a buffer 2202, a signal discoverycorrelator 2204 and a plurality of SOI RX processing cards 2206 ₁, 2206₂. During operation, the receiver 2200 stores samples of a combinedco-channel signal in buffer 2202. The buffer samples are a dynamicmixture of noise and multiple signals. The buffer 2200 allows thereceiver 2200 to perform an iterative decoding process of each collidingco-channel signal. In this regard, the colliding co-channel signalsstored in buffer 2200 are processed during each iteration of therespective decoding process. In some scenarios, the co-channel signalsare frequency hop signals.

The samples stored in buffer 2202 are then used by signal discoverycorrelator 2204 to detect one or more co-channel signals. The signaldiscovery correlator 2204 operates in the same or similar manner as thatdescribed above in relation to the single user case, i.e., it detectsthe start time and stop time of each co-channel signal. In theembodiment shown in FIG. 22, two co-channel signals are detected in afirst iteration of the Turbo MUD process. Accordingly, the receiver 2200logically creates two SOI RX processing cards 2206 ₁, 2206 ₂, one foreach detected co-channel signal. In the more general case, N co-channelsignals could be detected in a first iteration in which case thereceiver 2200 logically creates N SOI RX processing cards, one for eachdetected co-channel signal.

Each processing card 2206 ₁, 2206 ₂ comprises a demodulator 2212 andsignal reconstructor 2210. The demodulator 2212 of processing card 2206₁ attempts to demodulate a first one of the two identified co-channelsignals. Similarly, the demodulator of processing card 2206 ₂ attemptsto demodulate a second one of the two identified co-channel signals. Thedemodulators 2212 perform some of the same or similar operations to thatdescribed above in relation to the single user case. More specifically,each demodulator 2212 processes the samples of the combined co-channelsignal containing the respective identified co-channel signal. Thisprocessing includes: removing a frequency offset; performing matchfiltering operations; bit likelihood computations; and FEC decoding. Theoperations of demodulator 2212 will be described in more detail below inrelation to FIG. 25.

After the demodulator 2212 completes its processing, the signalreconstructor 2210 attempts to reconstruct an ideal copy of thetransmitted co-channel signal. The manner in which the transmittedco-channel signal is reconstructed will be described in detail below inrelation to FIG. 27. Still, it should be noted that the reconstructedsignal can be generated based on symbol likelihood values, which aredetermined from the bit likelihood values. In subsequent iterations ofthe Turbo MUD process, the reconstructed signal is used to removeinterference caused thereby to other co-channel signals. As a result,the subsequent demodulation and reconstruction processes have animproved performance during the subsequent iteration thereof.

Referring now to FIG. 23, there is provided a block diagram of anexemplary architecture for the receiver 2200 performing a subsequentpass (e.g., a second or third pass) of a Turbo MUD process in accordancewith the present invention. The receiver 2200 is able to discoveradditional users or co-channel signals in subsequent passes. In thisregard, the receiver 2200 subtracts the interference caused by thepreviously detected signals from the combined co-channel signal outputfrom buffer 2202. Thereafter, the receiver 2200 performs correlationoperations using the resulting signal with the interference removedtherefrom. During the correlation operations, the receiver 2200 detectsco-channel signals that are weaker than those co-channel signalspreviously detected. Every time a new co-channel signal is detected, thereceiver 2200 increments a count of the number of users that have beendiscovered. For example, if two users or two co-channel signals weredetected on a first pass, then N=2. If an additional user or co-channelsignal is detected during a second pass, then the value of N isincremented to N=3.

Thereafter, N logical SOI RX processing cards are required, one for eachdiscovered co-channel signal. In the above example, three SOI RXprocessing cards 2306 ₁, 2306 ₂, 2306 ₃ are required. Each processingcard 2306 ₁, 2306 ₂, 2306 ₃ is dedicated to one of the co-channelsignals which was detected during the correlation operations. Each SOIRX processing card treats its dedicated individual co-channel signal asthe SOI, while treating the other individual signals as interference. Asshown in FIG. 23, each processing card 2306 ₁, 2306 ₂, 2306 ₃ comprisesan interference canceller 2302, a demodulator 2304, and a signalreconstructor 2308. The interference canceller 2302 cancels theinterference from all other detected user or co-channel signals, exceptfor the co-channel signal to which the processing card is dedicated,which is the SOI for that processing card. For example, if N=3, then thethree processing cards 2306 ₁, 2306 ₂, 2306 ₃ are required. The firstprocessing card 2306 ₁ is dedicated to a first co-channel SOI, andtherefore cancels the interference caused to the first co-channel SOIfrom a second co-channel signal and a third co-channel signal. Thesecond processing card 2306 ₂ is dedicated to the second co-channel SOI,and thus cancels interference caused to the second co-channel SOI by thefirst co-channel signal and the third co-channel signal. Similarly, thethird processing card 2306 ₃ is dedicated to a third co-channel SOI, andcancels interference caused to the third co-channel SOI by the firstco-channel signal and the second co-channel signal. Embodiments of thepresent are not limited to the particularities of the example where N=3.Also, techniques for canceling signal interference are well known in theart. Any known or to be known interference cancelation technique can beused with the present invention without limitation. In some scenarios, asimple signal subtraction technique can be employed to removeinterference from a co-channel SOI.

Once the interference has been removed by the interference canceller2302, demodulation operations are performed thereon by demodulator 2304for its SOI. The output of the demodulator 2304 is then passed to thesignal reconstructor 2308. Demodulator 2304 is the same as or similar todemodulator 2212 of FIG. 22. Likewise, signal reconstructor 2308 is thesame as or similar to the signal reconstructor 2210 of FIG. 22. Thus,the discussion provided above in relation to components 2210, 2212 issufficient for understanding the operations of the demodulator 2304 andsignal reconstructor 2308. Still, it should be noted that the signalreconstructor 2308 reconstructs the samples of the co-channel SOI basedon the demodulator 2304 output for its SOI, but without knowledge oftheir amplitude and carrier phase. Therefore, additional operations areperformed to reconstruct the amplitude and carrier phase of theco-channel SOI. In this regard, the output of the signal reconstructor2308 comprises soft signal estimates without gain and phase adjustments.The soft signal estimates are then forwarded to a joint signalreconstructor 2310.

At the joint signal reconstructor 2310, a mathematical estimationtechnique is employed to jointly estimate the amplitude and carrierphase of all the detected co-channel signals. If the amplitude andcarrier phase are jointly estimated, then the accuracy of suchestimations is of a relatively high degree. The mathematical estimationtechnique generally involves a Least Squares Estimation which is alinear algebra technique. Once the amplitude and carrier phase has beendetermined, the N soft signal estimates are modified to produce N softsignal estimates with the determined gain and carrier phase. The N softsignal estimates are then forwarded to the signal discovery correlator2204 and interference canceller 2302 for use in the interferencesubtraction operations described above. Notably, the effectiveness ofthe interference subtraction operations usually increases on each passor iteration of the Turbo MUD processing.

Referring now to FIG. 24, there is provided a schematic illustrationthat is useful in understanding what happens when a receiversuccessfully recovers the bits of a detected co-channel signal. Once aCRC test succeeds, the data is known for the respective co-channelsignal. Accordingly, no more data detection is needed for thisco-channel signal. As such, the data is stored in a data store for usein all subsequent Turbo iterations, as shown in FIG. 24. The reason thatthe processing card continues to Turbo iterate is that the CRC′d signalstill acts as interference to other signals. Therefore, the co-channelsignal will continue to be used to eliminate interference caused therebyto the other detected co-channel signals for which a successful CRC testhas not been performed. Since the associated parameter estimates are notperfect (e.g., amplitude, timing, carrier phase, and frequency offset),the ability to eliminate interference caused by the known co-channelsignal is limited to the parameter accuracy. So, during each pass of theTurbo MUD process, the parameters are estimated by the demodulatorafresh with increasing accuracy. This allows the signal to bereconstructed and interference to be cancelled more precisely withfurther Turbo iterations. Strong interference must be suppressed many dBto discover and receive weak co-channel signals.

Referring now to FIG. 25, there is provided a more detailed blockdiagram of an exemplary demodulator 2500. Demodulator 2212 of FIG. 22and demodulator 2304 of FIG. 23 are the same as or similar todemodulator 2500. As such, the discussion provided herein in relation todemodulator 2500 is sufficient for understanding demodulators 2212,2304.

As shown in FIG. 25, demodulator 2500 is configured to receive theco-channel signal of interest 2502 and the other detected co-channelsignal estimates 2504. Co-channel signal 2502 has other userinterference and noise. As such, amble correlation 2506 is performed foreach co-channel signal to estimate the amplitude, fine sample timing,carrier phase and frequency offset. Also, a new matched filter isselected or designed based on the results of the amble correlation forits co-channel SOI, as described above in relation to the single usercase. In block 2508, the frequency offset is removed and the carrierphase is corrected. Thereafter, in block 2510, matched filtering for theco-channel SOI is performed on the output of block 2508. In a next block2512, bit likelihood values are computed for each SINR segment of theco-channel signal of interest, as described above in relation to FIG. 21and described below in relation to FIG. 26. Following the operations ofblock 2512, various other signal processing operations are performed forthe co-channel SOI, such as de-interleaving in block 2514, FEC decodingin block 2516 and CRC checking in block 2518. The operations of blocks2514, 2516, 2518 are the same as or substantially similar to that ofblocks 1016, 1018, 1020 of FIG. 10, respectively. As such, thediscussion provided above in relation to blocks 1016, 1018, 1020 issufficient for understanding the operations of blocks 2514, 2516, 2518.

Referring now to FIG. 26, there is provided a block diagram that isuseful for understanding how a bit likelihood determination is made inblock 2512 by demodulator 2500. As shown in FIG. 26, block 2512 isconfigured to divide the co-channel signal of interest into a pluralityof SINR segments (e.g., SINR segments 2102-2106 of FIG. 21), as shown byblock 2602 of FIG. 26. This signal segmentation is achieved using timingof other users or co-channel signals (i.e., start and stop times). Next,a noise and interference power or variance is computed for each SINRsegment in block 2604. The noise and interference power or variancevalues are then used to determine bit likelihood estimations overrespective segments, as shown by block 2606. The bit likelihoodestimations are determined in the same or similar manner to thatdescribed above in relation to the single user case (e.g., block 1014 ofFIG. 10). Where SINR is high (low), bit estimation confidence will behigh (low).

Referring now to FIG. 27, there is provided a block diagram that isuseful for understanding how soft signal estimates are generated by asignal reconstructor 2700 of a SOI RX processing card (e.g., processingcard 2210 of FIG. 22, processing card 2206 ₁, 2206 ₂ of FIG. 22 orprocessing card 2306 ₁, 2306 ₂, 2306 ₃ of FIG. 23) when a successful CRCcheck has not yet occurred. As shown in FIG. 27, the signalreconstructor 2700 is generally configured to perform similar operationsperformed by a transmitter. In this regard, the reconstructor 2700converts the coded bit likelihood values into soft coded bits in block2708. The soft coded bits have a mathematical property that is optimal.

The conversion operations of block 2708 will now be described in moredetail in relation to a graph 2900 of FIG. 29. Graph 2900 plots soft bitexpected values versus log likelihood ratios, an approximation of theequation b=tan h(γ/2), where b is the soft bit and γ is the loglikelihood ratio. As shown by graph 2900, if the bit likelihood has avalue of zero, then the soft reconstructed bit value is set equal tozero. If the bit likelihood has a value of positive eight, then the softreconstructed bit value is set equal to a positive one. If the bitlikelihood has a value of negative eight, then the soft reconstructedbit value is set equal to a negative one, and so on. Accordingly, thesignal reconstructor 2700 is converting the bit likelihood values tosoft bit expected values, i.e., the expected value of the bit symbol ata given point in time, where a bit symbol with a positive value mayrepresent a bit with a value of 1, and a bit symbol with a negativevalue may represent a bit with a value of 0.

Referring again to FIG. 27, the bits are shuffled in block 2710 so as tocreate a more uniform distribution of errors. Soft modulation is thenperformed in block 2714 using the shuffled bits to produce soft symbolsamples. The soft modulation can include, but is not limited to, BPSK,GSM like GMSK or QPSK. The output of block 2714 is passed to block 2716.Notably, blocks 2716-2720 are provided for purposes of matching certaincharacteristics of the modulated soft symbol samples with those of thesamples stored in a buffer (e.g., buffer 2202 of FIGS. 22-23).Accordingly, fine time staggering is achieved in block 2716. A frequencyoffset is then added in block 2718. In block 2720, all sample timing iscoarsely adjusted to match the timing of the corresponding samplesstored in the buffer (i.e., such that the start/stop time of theco-channel signal of interest matches that of the respective co-channelsignal contained in the combined co-channel signal stored in thebuffer).

Referring now to FIG. 28, there is provided a block diagram that isuseful for understanding how signal estimates are generated by a signalreconstructor 2800 of an SOI RX processing card (e.g., processing card2210 of FIG. 22, processing card 2206 ₁, 2206 ₂ of FIG. 22 or processingcard 2306 ₁, 2306 ₂, 2306 ₃ of FIG. 23) when a successful CRC check hasoccurred, so that the detected coded bits are known with near certaintyand are represented and stored with an arithmetic value of one (forbit=1) or negative one (for bit=0). As shown in FIG. 28, the signalreconstructor 2800 is configured to receive stored coded bits 2802. Eachcoded bit 2802 comprises a hard bit with a value of one or negative one.Bit confidence is not used by signal reconstructor 2800 because the CRCcheck was successful, and therefore the receiver is very confident thatthe values of coded bits 2802 are correct. The coded bits 2802 are thenprocessed in blocks 2810-2820. The operations of blocks 2810-2820 arethe same as or similar to those of blocks 2710-2720 of FIG. 27. As such,the discussion provided above in relation to blocks 2710-2720 issufficient for understanding blocks 2810-2820.

Referring now to FIG. 30, there is provided a schematic illustrationthat is useful for understanding a joint amplitude and carrier phaseestimation performed by a joint signal reconstructor (e.g., joint signalreconstructor 2310 of FIG. 23). As shown in FIG. 30, the buffer samplescomprise a mixture of noise and co-channel signals. The co-channelsignals are shifted left or right in the buffer depending upon theirstart times. The input into the joint signal reconstructor comprisesestimates of the reconstructed co-channel signals. The estimates of thereconstructed signals are then compared to the samples stored in thebuffer for purposes of jointly determining optimal estimates foramplitude and carrier phase. The unknown amplitude and carrier phase foreach co-channel signal is equal to an unknown complex constant. Theunknown constant is defined by the following mathematical equation (6).

C=Ae ^(jθ) =a+j*b  (6)

where C represents the unknown complex constant specifying the amplitudeand carrier phase of a co-channel signal. a represents a real componentof the complex constant C. b represents an imaginary component of thecomplex constant C.

The complex constant for the co-channel signals can be jointly solvedusing simple matrix algebra. As an example, for three signals, a matrixinverse is computed for a 3×3 matrix. An example of such a 3×3 matrixwill now be described in relation to FIG. 31. As shown in FIG. 31, ajoint reconstructor 3100 processes buffer samples r(n) and softco-channel signal estimates y₁, y₂, y₃ to generate 3 modified softco-channel signal estimates with gain and carrier phase adjustmentsC₁*y₁, C₂*y₂, C₃*y₃. The buffer samples r(n) are defined by thefollowing mathematical equation (7).

$\begin{matrix}{{r(n)} = {{\sum\limits_{i = 1}^{3}{C_{i}{y_{i}(n)}}} + {v(n)}}} & (7)\end{matrix}$

where C_(i) represents a complex constant. y_(i)(n) represents areconstructed soft co-channel signal estimate. v(n) represents noise.Notably, mathematical equation (7) shows that the value of i is 1, 2 or3 indicating that three users or co-channel signals were previouslydetected. The value of i is not limited in this regard, and can inprinciple have any integer value in accordance with how many users orco-channel signals have been previously detected. The values of thecomplex constants C_(i) in a three user case can be computed by solvingthe following matrix equation (8).

$\begin{matrix}{{\begin{bmatrix}{y_{1}(1)} & {y_{2}(1)} & {y_{3}(1)} \\{y_{1}(2)} & {y_{2}(2)} & {y_{3}(2)} \\\vdots & \vdots & \vdots \\{y_{1}(M)} & {y_{2}(M)} & {y_{3}(M)}\end{bmatrix}\begin{bmatrix}C_{1} \\C_{2} \\C_{3}\end{bmatrix}} = \begin{bmatrix}{r(1)} \\{r(2)} \\\vdots \\{r(M)}\end{bmatrix}} & (8)\end{matrix}$

where at least a portion of y₁(1), y₁(2), . . . y₁(M) in the firstcolumn of the M×3 matrix represent the reconstructed samples output froma first SOI RX processing card. At least a portion of y₂(1), y₂(2), . .. , y₂(M) in the second column of the M×3 matrix represent thereconstructed samples output from a second SOI RX processing card. Atleast a portion of y₃(1), y₃(2), . . . y₃(M) in a third column of theM×3 matrix represent the reconstructed samples output from a third SOIRX processing card. Any remaining values of y₁(1), y₁(2), . . . y₁(M),y₂(1), y₂(2), . . . y₂(M), y₃(1), y₃(2), . . . y₃(M) are set to zero,i.e., the samples before a co-channel signal begins or after aco-channel signal ends are set to zero so as to provide the samestaggering of the co-channel signals relative to that of the buffersamples. C₁ represents a complex constant for a first co-channel signal.C₂ represents a complex constant for a second co-channel signal. C₃represents a complex constant for a third co-channel signal. The vectorincluding C₁, C₂, C₃ is a 3×1 vector. r(1), r(2), . . . , r(M) representthe samples stored in a buffer. M can be any integer value. The vectorincluding r(1), r(2), . . . , r(M) is an M×1 vector.

Mathematical equation (8) can be rewritten as mathematical equation (9).

Yc=r  (9)

where Y represents the M×3 matrix of mathematical equation (8). crepresents the 3×1 vector of mathematical equation (8). r represents theM×1 vector of mathematical equation (8). For the three co-channel signalcase, the solution is obtained with a 3×3 matrix inverse, even if thenumber of buffer samples M is relatively large (e.g., 500). In thisregard, mathematical equation (9) can be rewritten as mathematicalequation (10).

(Y ^(H) Y)c=(Y ^(H) r)  (10)

where Y^(H) represents a conjugate transpose of the M×3 matrix Y.Mathematical equation (10) can be rewritten as mathematical equation(11).

Rc=d  (11)

where R represents Y^(H)Y, i.e., the correlation matrix of three usersor co-channel signals. d represents Y^(H)r. R is a 3×3 matrix, c is a3×1 vector and d is a 3×1 vector. As such, c can be solved in accordancewith the following relatively simple mathematical equation (12).

c=R ⁻¹ d  (12)

where R⁻¹ represents the inverse of matrix R. Inverting a 3×3 matrix isrelatively straightforward and computationally easy. One skilled in theart may recognize that there are a number of methods for estimating c inmathematical equation (10).

Referring now to FIGS. 32-33, there is provided schematic illustrationsthat are useful for understanding how soft symbols (bits) can be usedfor soft symbol modulation (e.g., block 2714 of FIG. 27 or block 2814 ofFIG. 28) of a signal reconstructor (e.g., signal reconstructor 2700 ofFIG. 27 or 2800 of FIG. 28). FIG. 32 provides an exemplary hard symbol(bit) modulator and an exemplary soft symbol (bit) modulator for BPSK.FIG. 33 provides an exemplary hard symbol (bit) modulator and anexemplary soft symbol (bit) modulator for QPSK.

In the BPSK scenario, the hard bit modulator, for example, represents abit value of one as positive one and a bit value of zero as a minus one.When the ones and zeros are to be transmitted, the hard bit modulatorsends impulses, each having an amplitude of plus one or minus one,through a pulse shaping filter to synthesize a waveform to betransmitted. The waveform is then converted onto an RF carrier andtransmitted from an antenna element.

However, in the Turbo MUD process of the present invention, bit andsymbol confidence information is used. Therefore, in the presentinvention, the co-channel signals are reconstructed using optimal bitand symbol confidence information. Symbol confidence information can bederived based on knowledge of all bit confidence information for thebits that comprise the symbol, which is a particularly trivial operationfor the case of modulations that utilize one coded bit per symbol. Thesignal reconstruction is achieved by creating impulses having magnitudesproportional to the symbol confidence levels thereof, respectively. Insome scenarios, an impulse magnitude is equal to a respective symbol'sexpected value. In Turbo MUD, soft reconstruction is important for softinterference cancelation. An interference symbol will be confidentlysubtracted when the risk is very low that it is wrong. Or, aninterference symbol will be weakly subtracted when the risk is high thatit is wrong.

In the QPSK scenario, the hard symbol (bit) modulator represents a firstbit per symbol as an imaginary component of an impulse having amagnitude of plus or minus one, and a second bit per symbol as a realcomponent of an impulse having a magnitude of plus or minus j. Theimpulses are sent through a pulse shaping filter to synthesize awaveform to be transmitted. The waveform is then converted onto an RFcarrier and transmitted from an antenna element.

However, in the Turbo MUD process of the present invention, bit andsymbol confidence information is used. Therefore, in the presentinvention, the co-channel signals are reconstructed using optimal bitand symbol confidence information. This signal reconstruction isachieved by creating impulses having complex magnitudes proportional tothe symbol confidence levels thereof, respectively.

Referring now to FIG. 34, there is provided a block diagram that isuseful for understanding the correlation operations of a correlator(e.g., signal discovery correlator 2204 of FIGS. 22-23) of a receiver(e.g., receiver 2200 of FIGS. 22-23). As noted above, new weakerco-channel signals can be discovered by subtracting the interferencecaused by all known existing N user signals. After the interference hasbeen removed, then the remaining signal is used for amble correlation todetect any new weaker co-channel signals.

Referring now to FIG. 35, there is provided a flow diagram of anexemplary method 3500 for receive processing of a burst communicationsystem where a plurality of co-channels signals collide in a receiver.The method 3500 begins with step 3502 and continues with step 3504. Instep 3504, at least a portion of a plurality of co-channel signals aresimultaneously received. The co-channel signals include signalstransmitted from a plurality of remote transmitters at a firstfrequency. Next, in step 3506, for example with N=2 users or co-channelsignals, each of a first and second co-channel signal is detected bycorrelating a pre-amble and a post-amble thereof. The pre-amble andpost-amble are then used in step 3508 to estimate an amplitude, acarrier phase, a frequency offset and/or a fine timing offset. Matchedfilters are designed in step 3510 for the first and second co-channelsignals. The matched filters are each designed using the respective finetiming offset.

Upon completing step 3510, step 3512 is performed where a firstiteration of a Turbo MUD process is independently performed for thefirst and second co-channel signals. As a result of performing the TurboMUD processes, best estimates for the first and second co-channelsignals are obtained. In the next step 3514 for the illustrativeexample, the best estimates are subtracted from a combined co-channelsignal such that a third co-channel signal can be detected which has asignal power weaker than a signal power of the first and secondco-channel signals. Thereafter, the third co-channel signal is detectedby correlating a pre-amble and a post-amble thereof, as shown by step3516.

Subsequent to detecting the third co-channel signal, an optional step3518 is performed. In step 3518, the best estimates are used to cancelinterference caused by (a) the first co-channel signal to the secondand/or third co-channel signals, and/or (b) the second co-channel signalto the first and/or third co-channel signals. Next, a first iteration ofthe Turbo MUD process is performed for the third co-channel signal, asshown by step 3520. Also, a second iteration of the Turbo MUD process isperformed for the first and second co-channel signals, as shown by step3522. Thereafter, step 3524 is performed where the method 3500 ends orother processing is performed.

Referring now to FIG. 36, there is provided a flow diagram of anexemplary Turbo MUD process 3600. The Turbo MUD process 3600 begins withstep 3602 and continues with step 3604. In step 3604, a co-channelsignal is segmented into a plurality of segments. Each segment has aunique SINR. Next in step 3606, a noise power or variance estimate iscomputed for each segment. The noise power or variances are then used instep 3608 to compute first bit likelihood values for the segments,respectively. Second bit likelihood values for each segment are computedin step 3610 using the first bit likelihood values (i.e., soft-insoft-out). The second bit likelihood values are used to generate a firstestimate of the co-channel signal, as shown by step 3612. The firstestimate is then used in step 3614 to jointly estimate amplitudes andcarrier phases for a plurality of co-channel signals, inclusive of theco-channel signal. The first estimate is modified in step 3616 toproduce a best estimate of the co-channel signal with the jointlyestimated amplitude and carrier phase. Thereafter, step 3618 isperformed where the method 3600 ends or other processing is performed.

All of the apparatus, methods and algorithms disclosed and claimedherein can be made and executed without undue experimentation in lightof the present disclosure. While the invention has been described interms of preferred embodiments, it will be apparent to those of skill inthe art that variations may be applied to the apparatus, methods andsequence of steps of the method without departing from the concept,spirit and scope of the invention. More specifically, it will beapparent that certain components may be added to, combined with, orsubstituted for the components described herein while the same orsimilar results would be achieved. All such similar substitutes andmodifications apparent to those skilled in the art are deemed to bewithin the spirit, scope and concept of the invention as defined.

We claim:
 1. A method for receive processing of a burst communicationsystem where a plurality of co-channels signals collide in a receiver,comprising: simultaneously receiving at least a portion of the pluralityof co-channel signals transmitted from a plurality of remotetransmitters at a first frequency; and independently performing a firstiteration of a Turbo MUD process for a first co-channel signal and asecond co-channel signal of the plurality of co-channel signals, saidTurbo MUD process comprising segmenting each of the first and secondco-channel signals into a plurality of segments each having a uniqueSignal to Interference plus Noise Ratio, computing a noise varianceestimate for each of the plurality of segments, computing first bitlikelihood values for each of the segments based on the noise varianceestimate, computing second bit likelihood values for each of thesegments based on the first bit likelihood values, and using the secondbit likelihood values to generate a first estimate of the first andsecond co-channel signals.
 2. The method according to claim 1, whereinthe Turbo MUD process further comprises detecting each of the firstco-channel signal and the second co-channel signal by correlating apre-amble and a post-amble thereof.
 3. The method according to claim 2,wherein the Turbo MUD process further comprises using the pre-amble andpost-amble of each first and second co-channel signal to estimate atleast one of an amplitude, a carrier phase, a frequency offset, and afine timing offset.
 4. The method according to claim 3, wherein theTurbo MUD process further comprises designing a matched filter for eachof the first and second co-channel signals using the estimates of thefine timing offset, respectively.
 5. The method according to claim 1,wherein each of the first and second co-channel signals is segmented by:detecting start times and stop times of the first and second co-channelsignals; and using the start times and stop times to determine overlapconditions of the first and second co-channel signals.
 6. The methodaccording to claim 1, wherein the Turbo MUD process further comprisessubtracting best estimates of the first and second co-channel signalsfrom a combined co-channel signal such that a third co-channel signalcan be detected which has a signal power weaker than a signal power ofthe first and second co-channel signals.
 7. The method according toclaim 6, further comprising independently Turbo MUD processing the thirdco-channel signal.
 8. The method according to claim 1, furthercomprising cancelling interference caused by the second co-channelsignal to the first co-channel signal prior to a second iteration of theTurbo MUD process for the first co-channel signal.
 9. The methodaccording to claim 1, wherein the first estimate is a soft signalestimate without gain and carrier phase adjustments.
 10. The methodaccording to claim 1, further comprising using the first estimate tojointly estimate an amplitude and a carrier phase of the first andsecond co-channel signals.
 11. The method according to claim 10, furthercomprising modifying the first estimate to produce a second estimatewith the jointly estimated amplitude and carrier phase.
 12. The methodaccording to claim 11, further comprising using the second estimate in asubsequent iteration of the Turbo MUD process for interferencecancellation and amble correlation.
 13. The method according to claim10, wherein the gain and carrier phase are jointly estimated for thefirst and second co-channel signals using Least Squares Estimation. 14.The method according to claim 13, wherein the Least Squares Estimationis performed by solving the following mathematical equationc=R ⁻¹ d where c represents a matrix of complex constants eachspecifying the gain and carrier phase for a respective one of the firstand second co-channel signals, R⁻¹ represents an inverse correlationmatrix of a plurality of users, d represents a product of multiplying avector including samples stored in a buffer and a conjugate transpose ofa matrix comprising reconstructed samples output from the Turbo MUDprocess for the first and second co-channel signals.
 15. A system,comprising: at least one electronic circuit configured to simultaneouslyreceive at least a portion of a plurality of co-channel signalstransmitted from a plurality of remote transmitters at a firstfrequency; and independently perform a first iteration of a Turbo MUDprocess for a first co-channel signal and a second co-channel signal ofthe plurality of co-channel signals, said Turbo MUD process comprisingsegmenting each of the first and second co-channel signals into aplurality of segments each having a unique Signal to Interference plusNoise Ratio, computing a noise variance estimate for each of theplurality of segments, computing first bit likelihood values for each ofthe segments based on the noise variance estimate, computing second bitlikelihood values for each of the segments based on the first bitlikelihood values, and using the second bit likelihood values togenerate a first estimate of the first and second co-channel signals.16. The system according to claim 15, wherein the Turbo MUD processfurther comprises detecting each of the first co-channel signal and thesecond co-channel signal by correlating a pre-amble and a post-amblethereof.
 17. The system according to claim 16, wherein the Turbo MUDprocess further comprises using the pre-amble and post-amble of eachfirst and second co-channel signal to estimate at least one of anamplitude, a carrier phase, a frequency offset, and a fine timingoffset.
 18. The system according to claim 17, wherein the Turbo MUDprocess further comprises designing a matched filter for each of thefirst and second co-channel signals using the estimates of the finetiming offset, respectively.
 19. The system according to claim 15,wherein each of the first and second co-channel signals is segmented by:detecting start times and stop times of the first and second co-channelsignals; and using the start times and stop times to determine overlapconditions of the first and second co-channel signals.
 20. The systemaccording to claim 15, wherein the Turbo MUD process further comprisessubtracting best estimates of the first and second co-channel signalsfrom a combined co-channel signal such that a third co-channel signalcan be detected which has a signal power weaker than a signal power ofthe first and second co-channel signals.
 21. The system according toclaim 20, wherein the electronic circuit is further configured toindependently Turbo MUD process the third co-channel signal.
 22. Thesystem according to claim 15, wherein the electronic circuit is furtherconfigured to cancel interference caused by the second co-channel signalto the first co-channel signal prior to a second iteration of the TurboMUD process for the first co-channel signal.
 23. The system according toclaim 15, wherein the first estimate is a soft signal estimate withoutgain and carrier phase adjustments.
 24. The system according to claim15, wherein the electronic circuit is further configured to use thefirst estimate to jointly estimate an amplitude and a carrier phase ofthe first and second co-channel signals.
 25. The system according toclaim 24, wherein the electronic circuit is further configured to modifythe first estimate to produce a second estimate with the jointlyestimated amplitude and carrier phase.
 26. The system according to claim25, further comprising using the second estimate in a subsequentiteration of the Turbo MUD process for interference cancellation andamble correlation.
 27. The system according to claim 24, wherein thegain and carrier phase are jointly estimated for the first and secondco-channel signals using Least Squares Estimation.
 28. The systemaccording to claim 27, wherein the Least Squares Estimation is definedby the following mathematical equationc=R ⁻¹ d where c represents a matrix of complex constants eachspecifying the gain and carrier phase for a respective one of the firstand second co-channel signals, R⁻¹ represents a correlation matrix of aplurality of users, d represents a product of multiplying a vectorincluding samples stored in a buffer and a conjugate transpose of amatrix comprising reconstructed samples output from the Turbo MUDprocess for the first and second co-channel signals.
 29. A method forreceive processing of a burst communication system where a plurality ofco-channels signals collide in a receiver, comprising: simultaneouslyreceiving at least a portion of the plurality of co-channel signalstransmitted from a plurality of remote transmitters at a firstfrequency; and independently performing a first iteration of a Turbo MUDprocess for a first co-channel signal of the plurality of co-channelsignals, said Turbo MUD process comprising segmenting the firstco-channel signal into a plurality of segments each having a uniqueSignal to Interference plus Noise Ratio, computing a noise varianceestimate for each of the plurality of segments, computing first bitlikelihood values for each of the segments based on the noise varianceestimate, computing second bit likelihood values for each of thesegments based on the first bit likelihood values, and using the secondbit likelihood values to generate a first estimate of the firstco-channel signal.